/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package com.zhaohg.spark.examples.sql;

// $example on:schema_merging$

import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.api.java.function.MapFunction;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Encoders;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.SparkSession;

import java.io.Serializable;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.Properties;

// $example off:schema_merging$
// $example on:basic_parquet_example$
// $example on:schema_merging$
// $example on:json_dataset$
// $example off:json_dataset$
// $example off:schema_merging$
// $example off:basic_parquet_example$

public class JavaSQLDataSourceExample {
    
    public static void main(String[] args) {
        SparkSession spark = SparkSession
                .builder()
                .appName("Java Spark SQL data sources example")
                .config("spark.some.config.option", "some-value")
                .getOrCreate();
        
        runBasicDataSourceExample(spark);
        runBasicParquetExample(spark);
        runParquetSchemaMergingExample(spark);
        runJsonDatasetExample(spark);
        runJdbcDatasetExample(spark);
        
        spark.stop();
    }
    // $example off:schema_merging$
    
    private static void runBasicDataSourceExample(SparkSession spark) {
        // $example on:generic_load_save_functions$
        Dataset<Row> usersDF = spark.read().load("zhaohg-spark/src/main/resources/users.parquet");
        usersDF.select("name", "favorite_color").write().save("namesAndFavColors.parquet");
        // $example off:generic_load_save_functions$
        // $example on:manual_load_options$
        Dataset<Row> peopleDF =
                spark.read().format("json").load("zhaohg-spark/src/main/resources/people.json");
        peopleDF.select("name", "age").write().format("parquet").save("namesAndAges.parquet");
        // $example off:manual_load_options$
        // $example on:direct_sql$
        Dataset<Row> sqlDF =
                spark.sql("SELECT * FROM parquet.`zhaohg-spark/src/main/resources/users.parquet`");
        // $example off:direct_sql$
    }
    // $example off:schema_merging$
    
    private static void runBasicParquetExample(SparkSession spark) {
        // $example on:basic_parquet_example$
        Dataset<Row> peopleDF = spark.read().json("zhaohg-spark/src/main/resources/people.json");
        
        // DataFrames can be saved as Parquet files, maintaining the schema information
        peopleDF.write().parquet("people.parquet");
        
        // Read in the Parquet file created above.
        // Parquet files are self-describing so the schema is preserved
        // The result of loading a parquet file is also a DataFrame
        Dataset<Row> parquetFileDF = spark.read().parquet("people.parquet");
        
        // Parquet files can also be used to create a temporary view and then used in SQL statements
        parquetFileDF.createOrReplaceTempView("parquetFile");
        Dataset<Row> namesDF = spark.sql("SELECT name FROM parquetFile WHERE age BETWEEN 13 AND 19");
        Dataset<String> namesDS = namesDF.map(new MapFunction<Row, String>() {
            public String call(Row row) {
                return "Name: " + row.getString(0);
            }
        }, Encoders.STRING());
        namesDS.show();
        // +------------+
        // |       value|
        // +------------+
        // |Name: Justin|
        // +------------+
        // $example off:basic_parquet_example$
    }
    
    private static void runParquetSchemaMergingExample(SparkSession spark) {
        // $example on:schema_merging$
        List<Square> squares = new ArrayList<>();
        for (int value = 1; value <= 5; value++) {
            Square square = new Square();
            square.setValue(value);
            square.setSquare(value * value);
            squares.add(square);
        }
        
        // Create a simple DataFrame, store into a partition directory
        Dataset<Row> squaresDF = spark.createDataFrame(squares, Square.class);
        squaresDF.write().parquet("data/test_table/key=1");
        
        List<Cube> cubes = new ArrayList<>();
        for (int value = 6; value <= 10; value++) {
            Cube cube = new Cube();
            cube.setValue(value);
            cube.setCube(value * value * value);
            cubes.add(cube);
        }
        
        // Create another DataFrame in a new partition directory,
        // adding a new column and dropping an existing column
        Dataset<Row> cubesDF = spark.createDataFrame(cubes, Cube.class);
        cubesDF.write().parquet("data/test_table/key=2");
        
        // Read the partitioned table
        Dataset<Row> mergedDF = spark.read().option("mergeSchema", true).parquet("data/test_table");
        mergedDF.printSchema();
        
        // The final schema consists of all 3 columns in the Parquet files together
        // with the partitioning column appeared in the partition directory paths
        // root
        //  |-- value: int (nullable = true)
        //  |-- square: int (nullable = true)
        //  |-- cube: int (nullable = true)
        //  |-- key: int (nullable = true)
        // $example off:schema_merging$
    }
    
    private static void runJsonDatasetExample(SparkSession spark) {
        // $example on:json_dataset$
        // A JSON dataset is pointed to by path.
        // The path can be either a single text file or a directory storing text files
        Dataset<Row> people = spark.read().json("zhaohg-spark/src/main/resources/people.json");
        
        // The inferred schema can be visualized using the printSchema() method
        people.printSchema();
        // root
        //  |-- age: long (nullable = true)
        //  |-- name: string (nullable = true)
        
        // Creates a temporary view using the DataFrame
        people.createOrReplaceTempView("people");
        
        // SQL statements can be run by using the sql methods provided by spark
        Dataset<Row> namesDF = spark.sql("SELECT name FROM people WHERE age BETWEEN 13 AND 19");
        namesDF.show();
        // +------+
        // |  name|
        // +------+
        // |Justin|
        // +------+
        
        // Alternatively, a DataFrame can be created for a JSON dataset represented by
        // an RDD[String] storing one JSON object per string.
        List<String> jsonData = Arrays.asList(
                "{\"name\":\"Yin\",\"address\":{\"city\":\"Columbus\",\"state\":\"Ohio\"}}");
        JavaRDD<String> anotherPeopleRDD = new JavaSparkContext(spark.sparkContext()).parallelize(jsonData);
        Dataset anotherPeople = spark.read().json(anotherPeopleRDD);
        anotherPeople.show();
        // +---------------+----+
        // |        address|name|
        // +---------------+----+
        // |[Columbus,Ohio]| Yin|
        // +---------------+----+
        // $example off:json_dataset$
    }
    
    private static void runJdbcDatasetExample(SparkSession spark) {
        // $example on:jdbc_dataset$
        // Note: JDBC loading and saving can be achieved via either the load/save or jdbc methods
        // Loading data from a JDBC source
        Dataset<Row> jdbcDF = spark.read()
                .format("jdbc")
                .option("url", "jdbc:postgresql:dbserver")
                .option("dbtable", "schema.tablename")
                .option("user", "username")
                .option("password", "password")
                .load();
        
        Properties connectionProperties = new Properties();
        connectionProperties.put("user", "username");
        connectionProperties.put("password", "password");
        Dataset<Row> jdbcDF2 = spark.read()
                .jdbc("jdbc:postgresql:dbserver", "schema.tablename", connectionProperties);
        
        // Saving data to a JDBC source
        jdbcDF.write()
                .format("jdbc")
                .option("url", "jdbc:postgresql:dbserver")
                .option("dbtable", "schema.tablename")
                .option("user", "username")
                .option("password", "password")
                .save();
        
        jdbcDF2.write()
                .jdbc("jdbc:postgresql:dbserver", "schema.tablename", connectionProperties);
        // $example off:jdbc_dataset$
    }
    
    // $example on:schema_merging$
    public static class Square implements Serializable {
        private int value;
        private int square;
        
        // Getters and setters...
        // $example off:schema_merging$
        public int getValue() {
            return value;
        }
        
        public void setValue(int value) {
            this.value = value;
        }
        
        public int getSquare() {
            return square;
        }
        
        public void setSquare(int square) {
            this.square = square;
        }
        // $example on:schema_merging$
    }
    
    // $example on:schema_merging$
    public static class Cube implements Serializable {
        private int value;
        private int cube;
        
        // Getters and setters...
        // $example off:schema_merging$
        public int getValue() {
            return value;
        }
        
        public void setValue(int value) {
            this.value = value;
        }
        
        public int getCube() {
            return cube;
        }
        
        public void setCube(int cube) {
            this.cube = cube;
        }
        // $example on:schema_merging$
    }
}
